BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1008 related articles for article (PubMed ID: 29704196)

  • 1. Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.
    Ross T; Zimmerer D; Vemuri A; Isensee F; Wiesenfarth M; Bodenstedt S; Both F; Kessler P; Wagner M; Müller B; Kenngott H; Speidel S; Kopp-Schneider A; Maier-Hein K; Maier-Hein L
    Int J Comput Assist Radiol Surg; 2018 Jun; 13(6):925-933. PubMed ID: 29704196
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation.
    Xiao Z; Su Y; Deng Z; Zhang W
    Comput Methods Programs Biomed; 2022 Nov; 226():107099. PubMed ID: 36116398
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.
    Burton W; Myers C; Rullkoetter P
    Comput Methods Programs Biomed; 2020 Jun; 189():105328. PubMed ID: 31958580
    [TBL] [Abstract][Full Text] [Related]  

  • 4. GAN-Based Image Colorization for Self-Supervised Visual Feature Learning.
    Treneska S; Zdravevski E; Pires IM; Lameski P; Gievska S
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214498
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Image generation by GAN and style transfer for agar plate image segmentation.
    Andreini P; Bonechi S; Bianchini M; Mecocci A; Scarselli F
    Comput Methods Programs Biomed; 2020 Feb; 184():105268. PubMed ID: 31891902
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning.
    Bencteux V; Saibro G; Shlomovitz E; Mascagni P; Perretta S; Hostettler A; Marescaux J; Collins T
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1585-1595. PubMed ID: 32592068
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Constrained-CNN losses for weakly supervised segmentation.
    Kervadec H; Dolz J; Tang M; Granger E; Boykov Y; Ben Ayed I
    Med Image Anal; 2019 May; 54():88-99. PubMed ID: 30851541
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Active learning using deep Bayesian networks for surgical workflow analysis.
    Bodenstedt S; Rivoir D; Jenke A; Wagner M; Breucha M; Müller-Stich B; Mees ST; Weitz J; Speidel S
    Int J Comput Assist Radiol Surg; 2019 Jun; 14(6):1079-1087. PubMed ID: 30968355
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Simulation-to-real domain adaptation with teacher-student learning for endoscopic instrument segmentation.
    Sahu M; Mukhopadhyay A; Zachow S
    Int J Comput Assist Radiol Surg; 2021 May; 16(5):849-859. PubMed ID: 33982232
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 3D deeply supervised network for automated segmentation of volumetric medical images.
    Dou Q; Yu L; Chen H; Jin Y; Yang X; Qin J; Heng PA
    Med Image Anal; 2017 Oct; 41():40-54. PubMed ID: 28526212
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Transfer learning for classification of cardiovascular tissues in histological images.
    Mazo C; Bernal J; Trujillo M; Alegre E
    Comput Methods Programs Biomed; 2018 Oct; 165():69-76. PubMed ID: 30337082
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification.
    Ribeiro E; Uhl A; Wimmer G; Häfner M
    Comput Math Methods Med; 2016; 2016():6584725. PubMed ID: 27847543
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Semi Supervised Learning with Deep Embedded Clustering for Image Classification and Segmentation.
    Enguehard J; O'Halloran P; Gholipour A
    IEEE Access; 2019; 7():11093-11104. PubMed ID: 31588387
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Contrastive self-supervised learning for diabetic retinopathy early detection.
    Ouyang J; Mao D; Guo Z; Liu S; Xu D; Wang W
    Med Biol Eng Comput; 2023 Sep; 61(9):2441-2452. PubMed ID: 37119374
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Self-Path: Self-Supervision for Classification of Pathology Images With Limited Annotations.
    Koohbanani NA; Unnikrishnan B; Khurram SA; Krishnaswamy P; Rajpoot N
    IEEE Trans Med Imaging; 2021 Oct; 40(10):2845-2856. PubMed ID: 33523807
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ReFs: A hybrid pre-training paradigm for 3D medical image segmentation.
    Xie Y; Zhang J; Liu L; Wang H; Ye Y; Verjans J; Xia Y
    Med Image Anal; 2024 Jan; 91():103023. PubMed ID: 37956551
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep virtual adversarial self-training with consistency regularization for semi-supervised medical image classification.
    Wang X; Chen H; Xiang H; Lin H; Lin X; Heng PA
    Med Image Anal; 2021 May; 70():102010. PubMed ID: 33677262
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Min-Max Similarity: A Contrastive Semi-Supervised Deep Learning Network for Surgical Tools Segmentation.
    Lou A; Tawfik K; Yao X; Liu Z; Noble J
    IEEE Trans Med Imaging; 2023 Oct; 42(10):2832-2841. PubMed ID: 37037256
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.
    Liu Y; He Q; Duan H; Shi H; Han A; He Y
    Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015814
    [TBL] [Abstract][Full Text] [Related]  

  • 20. GMIM: Self-supervised pre-training for 3D medical image segmentation with adaptive and hierarchical masked image modeling.
    Qi L; Jiang Z; Shi W; Qu F; Feng G
    Comput Biol Med; 2024 Jun; 176():108547. PubMed ID: 38728994
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 51.